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Actuarial science (assesses risk in the insurance and finance industries)

This function does not check whether the data points are at least interval apart.

CPython implementation detail: Under some circumstances, median_grouped() may coerce data points to floats. This behaviour is likely to change in the future.

See also

  • “Statistics for the Behavioral Sciences”, Frederick J Gravetter and Larry B Wallnau (8th Edition).
  • The SSMEDIAN function in the Gnome Gnumeric spreadsheet, including this discussion.

statistics.mode(data)

Return the most common data point from discrete or nominal data. The mode (when it exists) is the most typical value, and is a robust measure of central location.

If data is empty, or if there is not exactly one most common value, StatisticsError is raised.

mode assumes discrete data, and returns a single value. This is the standard treatment of the mode as commonly taught in schools:

>>> mode([1, 1, 2, 3, 3, 3, 3, 4])
3

The mode is unique in that it is the only statistic which also applies to nominal (non-numeric) data:

>>> mode(["red", "blue", "blue", "red", "green", "red", "red"])
'red'

statistics.pstdev(datamu=None)

Return the population standard deviation (the square root of the population variance). See pvariance() for arguments and other details.